Integration of lipidomics and transcriptomics data towards a systems biology model of sphingolipid metabolism

In this direction, the LIPID MAPS Consortium is developing methods to quantitate the sphingolipid metabolites in mammalian cells and is investigating their application to studies of the activation of the RAW264.7 macrophage cell by a chemically defined endotoxin, Kdo2-Lipid A. Herein, we describe a model for the C16-branch of sphingolipid metabolism (i.e., for ceramides with palmitate as the N-acyl-linked fatty acid, which is selected because it is a major subspecies for all categories of complex sphingolipids in RAW264.7 cells) integrating lipidomics and transcriptomics data and using a two-step matrix-based approach to estimate the rate constants from experimental data. The rate constants obtained from the first step are further refined using generalized constrained nonlinear optimization. The resulting model fits the experimental data for all species. The robustness of the model is validated through parametric sensitivity analysis.A quantitative model of the sphigolipid pathway is developed by integrating metabolomics and transcriptomics data with legacy knowledge. The model could be used to design experimental studies of how genetic and pharmacological perturbations alter the flux through this important lipid biosynthetic pathway.Sphingolipids (SL) are categorized as lipids with a sphingoid base backbone [1] that is often derivatized with an amide-linked fatty acid to make ceramides (Cer) and more structurally complex SL with diverse biological functions [2]. SL in essentially every subcategory, from the lipid backbones [3] to complex SL [4], are highly bioactive and play important roles in diseases [5,6]; hence, methods for "lipidomic" analysis of SL and SL metabolism are important for an in-depth understanding of these enigmatic compounds. In recent years, a number of large-scale experimental and bioinformatics projects have begun to address the complexity of the lipidome. Examples include the Lipid Metabolites and Pathways Strategy (LIPID MAPS) Consortium [7]